Incremental Vehicle 3-D Modeling from Video

In this paper, we present a new model-based approach for building 3D models of vehicles from color video provided by a traffic surveillance camera. We incrementally build 3D models using a clustering technique. Geometrical relations based on 3D generic vehicle model map 2D features to 3D. The 3D features are then adaptively clustered over the frame sequence to incrementally generate the 3D model of the vehicle. Results are shown for both simulated and real traffic video. They are evaluated by a new structural performance measure underscoring usefulness of incremental learning